Pub Date : 2019-12-01DOI: 10.1109/ICCES48960.2019.9068129
Eman Elemam, Ayman M. Bahaa-Eldin, N. Shaker, Mohamed Sobh
The Message Queue Telemetry Transport (MQTT) application layer protocol is widely used in Internet of Things (IoT) platforms. The MQTT standard has no mandatory requirements regarding the security services. A telemedicine is one of the IoT applications that mandates a critical level of security especially when it comes to human life. In this work, the weaknesses of MQTT are addressed and a modified protocol is proposed. This protocol mandates security aspects such as authentication, key exchange, and confidentiality. The protocol is proved to achieve its claims and is incorporated into a telemedicine environment as a critical environment for security.
{"title":"A Secure MQTT Protocol, Telemedicine IoT Case Study","authors":"Eman Elemam, Ayman M. Bahaa-Eldin, N. Shaker, Mohamed Sobh","doi":"10.1109/ICCES48960.2019.9068129","DOIUrl":"https://doi.org/10.1109/ICCES48960.2019.9068129","url":null,"abstract":"The Message Queue Telemetry Transport (MQTT) application layer protocol is widely used in Internet of Things (IoT) platforms. The MQTT standard has no mandatory requirements regarding the security services. A telemedicine is one of the IoT applications that mandates a critical level of security especially when it comes to human life. In this work, the weaknesses of MQTT are addressed and a modified protocol is proposed. This protocol mandates security aspects such as authentication, key exchange, and confidentiality. The protocol is proved to achieve its claims and is incorporated into a telemedicine environment as a critical environment for security.","PeriodicalId":136643,"journal":{"name":"2019 14th International Conference on Computer Engineering and Systems (ICCES)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116341831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-01DOI: 10.1109/ICCES48960.2019.9068110
Taha Emara, H. Afify, F. H. Ismail, A. Hassanien
Deep learning architectures, especially deep convolutional neural networks (CNN) achieve high accuracy on object classification and localization tasks. Achieving such high accuracy requires powerful devices. In this paper, rather than an ensemble of multiple complex models, a single Inception-v4 model is adapted to classify extracted from the HAM10000 dataset. The proposed model is enhanced by employing feature reuse using long residual connection in which the features extracted from earlier layers are concatenated with the high-level layers to increase the model classification performance. The dataset used in this study is imbalanced; therefore, a data sampling approach is used to mitigate the data imbalance effect. The proposed architecture achieves an accuracy of 94.7% using the provided test set at the official benchmark for the International Skin Imaging Collaboration (ISIC) 2018.
{"title":"A Modified Inception-v4 for Imbalanced Skin Cancer Classification Dataset","authors":"Taha Emara, H. Afify, F. H. Ismail, A. Hassanien","doi":"10.1109/ICCES48960.2019.9068110","DOIUrl":"https://doi.org/10.1109/ICCES48960.2019.9068110","url":null,"abstract":"Deep learning architectures, especially deep convolutional neural networks (CNN) achieve high accuracy on object classification and localization tasks. Achieving such high accuracy requires powerful devices. In this paper, rather than an ensemble of multiple complex models, a single Inception-v4 model is adapted to classify extracted from the HAM10000 dataset. The proposed model is enhanced by employing feature reuse using long residual connection in which the features extracted from earlier layers are concatenated with the high-level layers to increase the model classification performance. The dataset used in this study is imbalanced; therefore, a data sampling approach is used to mitigate the data imbalance effect. The proposed architecture achieves an accuracy of 94.7% using the provided test set at the official benchmark for the International Skin Imaging Collaboration (ISIC) 2018.","PeriodicalId":136643,"journal":{"name":"2019 14th International Conference on Computer Engineering and Systems (ICCES)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122879039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-01DOI: 10.1109/ICCES48960.2019.9068163
R. Shalaby, George A. Adib, Y. Sabry, Michael Gad, D. Khalil, Y. Sabry, D. Khalil
Silicon photonics is continuing to develop for an increasing number of applications including data centers, miniaturized sensors and atomic clocks. The development involved the creation of the technology platform, design of innovative devices and developing models and methods for fabrication tolerance assessment. In our work, we suggest a novel structure for silicon photonic coupled-ring-resonator with an order of scale difference in the rings' lengths and sensitivity analysis for this structure. The design consists of a long racetrack resonator of length 472.6 µm (sub-millimeter scale) nested by ring resonator of radius 25 µm, This radius was chosen to minimize bending losses. The coupling ratio of the directional couplers is designed to be 97/3. The suggested structure is fabricated by the IMEC fabrication facility which is using DUV lithography and silicon etching ePIXfab. The analysis shows that this structure can achieve higher finesse than the typical values of the conventional structure, even with reasonable fabrication tolerance. Experimentally a finesse of about 25 and a quality factor of about 17,000 is achieved. The proposed structure can improve the performance of optical sensing and filtering.
{"title":"Silicon photonic coupled-ring resonator in nested configuration comprising different length scales","authors":"R. Shalaby, George A. Adib, Y. Sabry, Michael Gad, D. Khalil, Y. Sabry, D. Khalil","doi":"10.1109/ICCES48960.2019.9068163","DOIUrl":"https://doi.org/10.1109/ICCES48960.2019.9068163","url":null,"abstract":"Silicon photonics is continuing to develop for an increasing number of applications including data centers, miniaturized sensors and atomic clocks. The development involved the creation of the technology platform, design of innovative devices and developing models and methods for fabrication tolerance assessment. In our work, we suggest a novel structure for silicon photonic coupled-ring-resonator with an order of scale difference in the rings' lengths and sensitivity analysis for this structure. The design consists of a long racetrack resonator of length 472.6 µm (sub-millimeter scale) nested by ring resonator of radius 25 µm, This radius was chosen to minimize bending losses. The coupling ratio of the directional couplers is designed to be 97/3. The suggested structure is fabricated by the IMEC fabrication facility which is using DUV lithography and silicon etching ePIXfab. The analysis shows that this structure can achieve higher finesse than the typical values of the conventional structure, even with reasonable fabrication tolerance. Experimentally a finesse of about 25 and a quality factor of about 17,000 is achieved. The proposed structure can improve the performance of optical sensing and filtering.","PeriodicalId":136643,"journal":{"name":"2019 14th International Conference on Computer Engineering and Systems (ICCES)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126310871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-01DOI: 10.1109/icces48960.2019.9068177
{"title":"Session MS: Modeling and Simulation","authors":"","doi":"10.1109/icces48960.2019.9068177","DOIUrl":"https://doi.org/10.1109/icces48960.2019.9068177","url":null,"abstract":"","PeriodicalId":136643,"journal":{"name":"2019 14th International Conference on Computer Engineering and Systems (ICCES)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125869318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-01DOI: 10.1109/ICCES48960.2019.9068136
H. Hussien
A combination of DNA computing and a genetic algorithm is announced for RGB image encryption. The model is strong based on the scrambling technique of DNA computing operations using the crossover and mutation process and establishing a dynamic key based on a genetic algorithm, including a set of parameters such as population size, number of generation and mutation probability. First, the decoding of the image GA selected DNA sequence encoding process and the random key for the three R G B channels were followed by the DNA addition process. The decoded DNA added to the matrix of the output. Finally, conduct the XOR-mod procedure on the decoded matrix and the random number of the genetic algorithm to obtain the encrypted image. The paper includes countless experimental steps to confirm that the model has a high degree of safety and strength against different types of attacks.
{"title":"DNA Computing for RGB image Encryption with Genetic Algorithm","authors":"H. Hussien","doi":"10.1109/ICCES48960.2019.9068136","DOIUrl":"https://doi.org/10.1109/ICCES48960.2019.9068136","url":null,"abstract":"A combination of DNA computing and a genetic algorithm is announced for RGB image encryption. The model is strong based on the scrambling technique of DNA computing operations using the crossover and mutation process and establishing a dynamic key based on a genetic algorithm, including a set of parameters such as population size, number of generation and mutation probability. First, the decoding of the image GA selected DNA sequence encoding process and the random key for the three R G B channels were followed by the DNA addition process. The decoded DNA added to the matrix of the output. Finally, conduct the XOR-mod procedure on the decoded matrix and the random number of the genetic algorithm to obtain the encrypted image. The paper includes countless experimental steps to confirm that the model has a high degree of safety and strength against different types of attacks.","PeriodicalId":136643,"journal":{"name":"2019 14th International Conference on Computer Engineering and Systems (ICCES)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133863101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-01DOI: 10.1109/ICCES48960.2019.9068112
Hussein M. Fawzy, H. El Sherif, A. Khamis
There is a considerable increase in the number of skyscrapers in the world due modern development of construction technology. Current maintenance work for high-rise buildings mostly uses conventional ropes and scaffolds that pose a high risk of accidents and exhibit poor performance and efficiency. There is a demand to develop an automated cleaning system that can reduce accidents and improve the maintenance efficiency of the conventional high-rise building façade maintenance systems. In this paper, we demonstrate an automated façade cleaning system that can reduce accidents and decrease labor costs. We propose a new technique of cleaning mechanism for façade cleaning in high-rise buildings; the system consists of two Robots working for the cleaning process; the lifting robot or the Roof Top Robot (RTR) and the Cleaning Robot (CR). The RTR is designed to lift the CR vertically on the façade in the upper and lower directions; the horizontal direction is also performed by the end of each vertical motion. The CR acts as the main cleaning unit, which utilizes different cleaning modules that is required for the cleaning quality. The performance of the proposed cleaning system is evaluated experimentally; however, additional study should be necessary for more complicated facades architect designs.
{"title":"Robotic Façade Cleaning System for High-Rise Building","authors":"Hussein M. Fawzy, H. El Sherif, A. Khamis","doi":"10.1109/ICCES48960.2019.9068112","DOIUrl":"https://doi.org/10.1109/ICCES48960.2019.9068112","url":null,"abstract":"There is a considerable increase in the number of skyscrapers in the world due modern development of construction technology. Current maintenance work for high-rise buildings mostly uses conventional ropes and scaffolds that pose a high risk of accidents and exhibit poor performance and efficiency. There is a demand to develop an automated cleaning system that can reduce accidents and improve the maintenance efficiency of the conventional high-rise building façade maintenance systems. In this paper, we demonstrate an automated façade cleaning system that can reduce accidents and decrease labor costs. We propose a new technique of cleaning mechanism for façade cleaning in high-rise buildings; the system consists of two Robots working for the cleaning process; the lifting robot or the Roof Top Robot (RTR) and the Cleaning Robot (CR). The RTR is designed to lift the CR vertically on the façade in the upper and lower directions; the horizontal direction is also performed by the end of each vertical motion. The CR acts as the main cleaning unit, which utilizes different cleaning modules that is required for the cleaning quality. The performance of the proposed cleaning system is evaluated experimentally; however, additional study should be necessary for more complicated facades architect designs.","PeriodicalId":136643,"journal":{"name":"2019 14th International Conference on Computer Engineering and Systems (ICCES)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134552169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-01DOI: 10.1109/ICCES48960.2019.9068128
A. Fekry, Georgios A. Dafoulas, Manal A. Ismail
This paper suggests a model for automatic detection of student behavior to be used in student presentations. The proposed approach is based on the combined use of computer vision libraries and machine learning algorithms to help and support in student assessment using video content. This paper is a part of a research study focusing on investigating and analysing, human behaviours and finding relations between human behaviours and their personal modalities using pattern recognition techniques. For the purpose of this study a group of specific behaviours expressed by students during group presentations in higher education level, are selected. The study proceeds with the detection of the occurrences of those behaviours and comparative analysis of the model's suggested behavioural patterns against those observed through the manual analysis of observations. Both approaches are based on the same set of video files.
{"title":"Automatic detection for students behaviors in a group presentation","authors":"A. Fekry, Georgios A. Dafoulas, Manal A. Ismail","doi":"10.1109/ICCES48960.2019.9068128","DOIUrl":"https://doi.org/10.1109/ICCES48960.2019.9068128","url":null,"abstract":"This paper suggests a model for automatic detection of student behavior to be used in student presentations. The proposed approach is based on the combined use of computer vision libraries and machine learning algorithms to help and support in student assessment using video content. This paper is a part of a research study focusing on investigating and analysing, human behaviours and finding relations between human behaviours and their personal modalities using pattern recognition techniques. For the purpose of this study a group of specific behaviours expressed by students during group presentations in higher education level, are selected. The study proceeds with the detection of the occurrences of those behaviours and comparative analysis of the model's suggested behavioural patterns against those observed through the manual analysis of observations. Both approaches are based on the same set of video files.","PeriodicalId":136643,"journal":{"name":"2019 14th International Conference on Computer Engineering and Systems (ICCES)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131884719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-01DOI: 10.1109/icces48960.2019.9068105
{"title":"Session AI2: Artificial Intelligence II","authors":"","doi":"10.1109/icces48960.2019.9068105","DOIUrl":"https://doi.org/10.1109/icces48960.2019.9068105","url":null,"abstract":"","PeriodicalId":136643,"journal":{"name":"2019 14th International Conference on Computer Engineering and Systems (ICCES)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131338991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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